Geospatial environmental accounting reference layers

GIS Map Application Published 21 Nov 2019 Last modified 21 Mar 2020
1 min read
The map viewer of the Integrated Data Platform visualizes spatial datasets by web map services. Those spatial datasets are selected which are frequently used in assessments. The web map viewer enables spatial overlays so that the datasets can be interactively explored. Through exploring the datasets their potentials in environmental assessments can be better understood.

More information

For exploring contextual details about the added datasets, please activate the information icon in the upper right corner. Legends of the added datasets can be explored by activating the legend icon.

Web map services are produced in ArcGIS desktop and visualized in ArcGIS Online. Once a web map service is quality controlled, the service is registered in the Spatial Data Infrastructure and read into the IDP Web Map Viewer.

The web application offers three main functions to the user for data exploration:

  1. Search for a web map service: the search uses 1) keywords (i.e. tags such as land use), or 2) topic names (such as biodiversity). The keywords are also searched in the abstract of the related spatial dataset, which is harvested from EEA`s Spatial Data Infrastructure (SDI). Hence, all datasets can be found which have e.g. Corine Land Cover in their abstract.

  2. The user is able to visualise and explore the web maps identified by the search function. Furthermore, selected web maps can be overlaid for further exploration of commonalities between spatial datasets.

  3. Once the wished services are found and explored by overlays and zoom functions, the user can find all relevant semantic information of the spatial datasets when activating the info button. These semantic information are combinations of technical information coming from the SDI and other semantics harvested from the content management system.

 

Related content

Based on data

Vegetation growing season length 2000-2016 The raster files are the annual above ground growing season length time-series and the derived linear trends for the period 2000-2016. The data set addresses trends in the season length of land surface vegetation derived from remote sensing observed time series of vegetation indices. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The Plant Phenology Index (PPI) is a new vegetation index optimized for efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in visible-red (RED) and near-infrared (NIR) spectral domains. PPI is defined to have a linear relationship to the canopy green leaf area index (LAI) and its temporal pattern is strongly similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. PPI is less affected by presence of snow compared to commonly used vegetation indices such as Normalized Difference Vegetation Index (NDVI) or Enhanced Vegetation Index (EVI). The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period.
Above ground vegetation productivity 2000-2016 The raster files are the above ground vegetation productivity time-series and the derived linear trend for the period 2000-2016.The data set addresses trends in land surface productivity derived from remote sensing observed time series of vegetation indices. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The Plant Phenology Index (PPI) is a new vegetation index optimized for efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in visible-red (RED) and near-infrared (NIR) spectral domains. PPI is defined to have a linear relationship to the canopy green leaf area index (LAI) and its temporal pattern is strongly similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. PPI is less affected by presence of snow compared to commonly used vegetation indices such as Normalized Difference Vegetation Index (NDVI) or Enhanced Vegetation Index (EVI).The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period.
Richness of forest-related species and habitats indicator 2012 dataset This dataset refers to the Richness index of Species and Habitats of Conservation Concern indicator. This indicator has been developed to be used as a sub-indicator for contributing to the identification of the High Nature Value (HNV) Forest Areas as it will be integrated with other sub-indicators of horizontal structure, management and naturalness to generate the final composite indicator. It is composed itself of three sub-indicators: “Forest Non-bird species”, “Forest bird species” and “Forest habitats”. All the three sub-indicators build on distribution data from the reporting of habitat and species conservation status under Article 17 of the Habitats Directive and Article 12 of the Birds directive which describe their distribution at 10km grid resolution. The forest species and the forest habitats proposed to be used for the HNV forest area identification were selected based on expert judgement (ETC/BD) and raster files reporting the count of forest species and habitats were created. At this stage, no weight is applied based on Habitat and Species prioritization, conservation status or endemism. The sub-indicators were then normalized for each European forest type and successively combined not assigning any specific weight to a particular sub-indicator. The values for this indicator, present in this dataset, ranges between 0 and 1. The values close to 1 mean high presence of habitats and species related to forest, whereas the lower richness are closer to 0. It covers the forested areas of the EU27 Member States except for Cyprus (data from Croatia will be reported starting from the next update regarding the period 2013-2018).
Management related pressures on forest ecosystems Forest management involves various degrees of human intervention to safeguard the forest ecosystem and its functions as well as the exploitation of forest resources. While the objectives of management vary widely and include the protection of resources in protected forests and nature reserves, the primary objective is mostly the production of wood products. Although sustained yield forestry continues to be widely practised, there is an increasing trend towards the management of forests as ecological systems with multiple economic benefits and environmental values, ensuring that benefits meet present as well as future generations’ needs. In order to assess forest management intensity in Europe an indicator based on three data sources has been developed: a) Fast track ecosystem capital accounts (forest growth & harvest – disaggregated to 1km grid), b) Potential forest management (gradient of intensity of intervention with the natural processes in a forest) c) Forest fragmentation (forest ecosystem network connected by forest bridges – GUIDOS Morphological Spatial Pattern Analysis). Each input dataset has been assessed separately in a first step in terms of pressures on forest ecosystems which are the result of the specific management, use or respectively state of the forest patch. The overall management related pressure is then derived by crossing the relative pressures by each input and evaluating the constellation of the input representative factors. This updated version of the management related forest pressures is based on the first assessment done in framework of the ETC-SIA report "Land use and land management related pressures on agricultural and forest ecosystems" (ETC-SIA, Task 1.8.4.3 Ecosystem pressures).

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